Is there a linear relationship between the dose of ruminant<i>trans</i>-fatty acids and cardiovascular risk markers in healthy subjects: results from a systematic review and meta-regression of randomised clinical trials
Bibliographic record
Abstract
The effects of ruminant (R) trans-fatty acids (TFA) on the risk of CVD are still under debate. It could be argued that the lack of the effect of R-TFA may be the result of the small amount of their intake. Taking into consideration the growing available data from intervention studies, we carried out a systematic review and meta-regression to assess the impact of R-TFA intake levels on changes in the total cholesterol: HDL-cholesterol (TC:HDL-C) ratio. A systematic review of the literature was conducted and thirteen randomised clinical trials were included, yielding a total of twenty-three independent experimental groups of subjects. A univariate random-effects meta-regression approach was used to quantify the relationship between the dose of R-TFA and changes in the TC:HDL-C ratio. To consider several potential modifiers such as subject and dietary characteristics, a multivariate regression analysis was performed. We found no relationship between R-TFA intake levels of up to 4.19% of daily energy intake (EI) and changes in cardiovascular risk factors such as TC:HDL-C and LDL-cholesterol (LDL-C):HDL-C ratios. In addition, a multivariate regression analysis that included other dietary variables, as well as subject baseline characteristics, confirmed that doses of R-TFA did not significantly influence the changes in the lipid ratio. Our findings showed that doses of R-TFA did not influence the changes in the ratios of plasma TC:HDL-C and LDL-C:HDL-C. These data suggest that TFA from natural sources, at least at the current levels of intake and up to 4.19% EI, have no adverse effects on these key CVD risk markers in healthy people.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.070 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".